{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quick example to smooth a signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/charles/miniconda3/envs/py36/lib/python3.6/site-packages/sklearn/ensemble/weight_boosting.py:29: DeprecationWarning: numpy.core.umath_tests is an internal NumPy module and should not be imported. It will be removed in a future NumPy release.\n",
      "  from numpy.core.umath_tests import inner1d\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "#import sys\n",
    "sys.path.append(\"../\")\n",
    "import numpy as np\n",
    "import scipy\n",
    "from matplotlib import pyplot as plt\n",
    "#import gcvspline\n",
    "import rampy as rp\n",
    "import gcvspline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating a fake, noisy signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "nb_points  = 200\n",
    "x = np.linspace(50, 600, nb_points)\n",
    "\n",
    "# gaussian peaks\n",
    "p1 = 20.0 * np.exp(-np.log(2) * ((x-150.0)/15.0)**2)\n",
    "p2 = 100.0 * np.exp(-np.log(2) * ((x-250.0)/20.0)**2)\n",
    "p3 = 50.0 * np.exp(-np.log(2) * ((x-450.0)/50.0)**2)\n",
    "p4 = 20.0 * np.exp(-np.log(2) * ((x-350.0)/300)**2)\n",
    "p5 = 30.0 * np.exp(-np.log(2) * ((x-460.0)/5.0)**2)\n",
    "\n",
    "# background: a large gaussian + linear \n",
    "bkg = 60.0 * np.exp(-np.log(2) * ((x-250.0)/200.0)**2) + 0.1*x\n",
    "\n",
    "#noise\n",
    "noise = 2.0 * np.random.normal(size=nb_points)\n",
    "\n",
    "#observation\n",
    "y = p1 + p2 + p3 + p4 + p5 + noise +bkg\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Smoothing the signal with the smooth() function\n",
    "\n",
    "The smooth function has 10 different smnoothings algorithms.\n",
    "\n",
    "Spline, Savitsky-Golay and Whittaker smoothing are available as:\n",
    "    - GCVSmoothedNSpline (Generalised Cross Validated Spline, see gcvspline doc)\n",
    "    - DOFSmoothedNSpline (Degree of Freedom spline, see gcvspline doc)\n",
    "    - MSESmoothedNSpline (Mean Square Error spline, see gcvspline doc)\n",
    "    - savgol, the scipy Savitsky-Golay filter\n",
    "    - whittaker, a Whittaker smoother (see also whittaker() function)\n",
    "\n",
    "Moving window smoothings are available by setting the method to:\n",
    "    - flat, a flat window smoothing\n",
    "    - hanning, a hanning window smoothing\n",
    "    - hamming, a hamming window smoothing\n",
    "    - bartlett, a bartlett window smoothing\n",
    "    - blackman, a blackman window smoothing\n",
    "    \n",
    "See the smooth function help for more details on parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/charles/miniconda3/envs/py36/lib/python3.6/site-packages/scipy/signal/_arraytools.py:45: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  b = a[a_slice]\n"
     ]
    }
   ],
   "source": [
    "y_smo_1 = rp.smooth(x,y,method=\"GCVSmoothedNSpline\")\n",
    "y_smo_2 = rp.smooth(x,y,method=\"DOFSmoothedNSpline\")\n",
    "y_smo_3 = rp.smooth(x,y,method=\"MSESmoothedNSpline\")\n",
    "y_smo_4 = rp.smooth(x,y,method=\"savgol\",window_length=5,polyorder=2)\n",
    "y_smo_5 = rp.smooth(x,y,method=\"whittaker\",Lambda=10**0.5)\n",
    "y_smo_6 = rp.smooth(x,y,method=\"flat\",window_length=5)\n",
    "y_smo_7 = rp.smooth(x,y,method=\"hanning\",window_length=5)\n",
    "y_smo_8 = rp.smooth(x,y,method=\"hamming\",window_length=5)\n",
    "y_smo_9 = rp.smooth(x,y,method=\"bartlett\",window_length=5)\n",
    "y_smo_10 = rp.smooth(x,y,method=\"blackman\",window_length=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Figures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f656457bb38>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "plt.subplot(2,1,1)\n",
    "plt.plot(x,y,\"k.\",label=\"signal\")\n",
    "plt.plot(x,y_smo_1,label=\"GCVSmoothedNSpline\")\n",
    "plt.plot(x,y_smo_2,label=\"DOFSmoothedNSpline\")\n",
    "plt.plot(x,y_smo_3,label=\"MSESmoothedNSpline\")\n",
    "plt.plot(x,y_smo_4,label=\"savgol\")\n",
    "plt.plot(x,y_smo_5,label=\"whittaker\")\n",
    "\n",
    "plt.xlabel(\"X\")\n",
    "plt.ylabel(\"Y\")\n",
    "plt.legend()\n",
    "\n",
    "plt.subplot(2,1,2)\n",
    "plt.plot(x,y,\"k.\",label=\"signal\")\n",
    "plt.plot(x,y_smo_6,label=\"flat\")\n",
    "plt.plot(x,y_smo_7,label=\"hanning\")\n",
    "plt.plot(x,y_smo_8,label=\"hamming\")\n",
    "plt.plot(x,y_smo_9,label=\"bartlett\")\n",
    "plt.plot(x,y_smo_10,label=\"blackman\")\n",
    "\n",
    "plt.xlabel(\"X\")\n",
    "plt.ylabel(\"Y\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
